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Data from: Fish assemblage convergence along stream environmental gradients: an intercontinental analysis


Bower, Luke M.; Winemiller, Kirk O. (2020), Data from: Fish assemblage convergence along stream environmental gradients: an intercontinental analysis, Dryad, Dataset,


Species that pass through similar environmental filters, regardless of geographic proximity or evolutionary history, are expected to share many traits, resulting in similar assemblage trait distributions. Convergence of assemblage trait distributions among different biotic regions would indicate that consistent ecological processes produce repeated patterns of adaptive evolution. This study analyzes trait-environment relationships across multiple stream fish assemblages representing evolutionarily divergent faunas. We hypothesized that trait-environment patterns converge across regional faunas in response to a common set of environmental filters acting on functional traits. One hundred and ninety-seven species and forty streams were sampled from five regions: Belize, Benin, Brazil, Cambodia, and United States of America. By examining trait-environment plots, multiple congruent trait-environment patterns were found across all regions, indicative of a consistent set of environmental filters acting on local community assembly. The consistency of these patterns strongly suggests that water velocity and habitat structural complexity function as universal environmental filters, producing similar assemblage trait distributions in streams across all regions. Bivariate relationships were not universal, and only one of the associations between a single functional trait and single environmental variable was statistically significant across all five regions. Strong phylogenetic signal was found in traits and habitat use, which implies that niche conservatism also influenced assemblage trait distributions. Overall, results support the idea that habitat templates structure trait distributions of stream fish assemblages and do so in a consistent manner.

Usage Notes


National Science Foundation, Award: DEB-1601687